NDLI: Lung field segmentation in chest radiographs: a historical review, current status, and expectations from deep learning

Content Provider	IET Digital Library
Author	Mittal, Ajay Hooda, Rahul Sofat, Sanjeev
Abstract	Lung field defines a region-of-interest in which specific radiologic signs such as septal lines, pulmonary opacities, cavities, consolidations, and lung nodules are searched by a chest radiographic computer-aided diagnostic system. Thus, its precise segmentation is extremely important. To precisely segment it, numerous methods have been developed during the last four decades. However, no exclusive survey consolidating the advancements in these methods has been presented till date, thus indicating a void and the need. This study fills the void by presenting a comprehensive survey of these methods with a focus on their underlying principle, the dataset used, reported performance, and relative merits and demerits. It refrains from doing a hard comparative evaluation by bringing all of them on a common platform, since the datasets used in their development and testing are of varied quality, complexity, and are not publicly available. It also provides a glimpse of deep learning, the present state of deep-learning-based lung field segmentation methods, expectations from it, and the challenges ahead of it.
Starting Page	937
Ending Page	952
Page Count	16
ISSN	17519659
Volume Number	11
e-ISSN	17519667
Issue Number	Issue 11, Nov (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/11/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.0526
Journal	IET Image Processing
Publisher Date	2017-07-07
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biology And Medical Computing Biomedical Imaging/measurement Chest Radiographic Computer-aided Diagnostic System Computer Vision And Image Processing Technique Deep Learning Diagnostic Radiography Image Segmentation Knowledge Engineering Technique Learning in AI Lung Lung Field Segmentation Medical Image Processing Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Radiography And Computed Tomography Radiologic Signs Region-of-interest X-Ray Technique X-Rays And Particle Beam
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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